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Case Based Reasoning using K-Nearest Neighbor with Euclidean Distance for Early Diagnosis of Personality Disorder Anna Hendri Soleliza Jones; Cicin Hardiyanti
IJISTECH (International Journal of Information System and Technology) Vol 5, No 1 (2021): June
Publisher : Sekolah Tinggi Ilmu Komputer (STIKOM) Tunas Bangsa

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30645/ijistech.v5i1.111

A personality disorder is a condition of a person with an extreme personality that causes the sufferer to have unhealthy and different thoughts patterns and behavior from other people. The personality disorders discussed in this study consisted of 110 diseases with 300 case data and 68 symptoms. Based on Basic Health Research (Riskesdas) 2018 data, it shows that more than 19 million people aged 15 years and over were affected by mental-emotional disorders. Data from the Statistics Indonesia in 2019 that the population of Indonesia is around 265 million people, while according to the Indonesian Clinical Psychologist Association, the number of verified professional psychologists is 1,599 clinical psychologists out of a total membership of 2,078 as of January 2019. However, this figure does not meet the standards of the World Health Organization (WHO), which is that psychologists serve 30 thousand people. This shows that Indonesia still lacks around 28,970 psychologists. The unequal distribution of professional psychologists has made psychologists need a long time to provide a diagnosis because of the number of patients being inversely proportional to the availability of psychologists in Indonesia. Moreover, there is not enough patient knowledge about the symptoms they feel. This study aims to produce a system for diagnosing personality disorders. This study is a case based reasoning to solve problems that have occurred in previous cases using K-Nearest Neighbor to classify data based on the closest distance using the calculation of the Euclidean Distance. Algorithm testing for the system used the Confusion Matrix test. Based on the results of testing data in the 60 case data using K-nearest Neighbor and the calculation of the Euclidean Distance with a score of K=3, it is known that 60 data have 100% similarity to cases with a personality disorder. Meanwhile, testing new cases with 10 case data that were not in the knowledge base was also conducted showing that 9 cases had 100% similarity to the previous case, while another case had 90% similarity to the previous case.

Fp-Growth Algorithm For Searching Book Borrowing Transaction Patterns And Study Program Suitability Lisna Zahrotun; Anna Hendri Soleliza Jones
IJISTECH (International Journal of Information System and Technology) Vol 5, No 5 (2022): February
Publisher : Sekolah Tinggi Ilmu Komputer (STIKOM) Tunas Bangsa

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30645/ijistech.v5i5.180

The current development of data has reached a sizeable amount. This is due to the development of the world of information technology which consists of data in it. One technique that can handle abundant data is data mining. Data mining methods are widely used to perform large amounts of data analysis. In the academic field, analysis can be used to determine the patterns of students and lecturers. Whereas in library transactions, analysis can be carried out to determine the patterns of existing book borrowing. This is done to determine the tendency of students with certain study programs to borrow any uku transactions. In this study, the aim of this research is to analyze the patterns of borrowing books from the Ahmad Dahlan University library, which includes borrowing transaction data and the book owner's study program. In addition, in this study, a percentage analysis of the suitability of the book borrower study program and the book owner's study program was also carried out. The stages in this research include data collection, data cleaning, data selection, data transformation, searching for association patterns using the FP-Growth method and pattern evaluation. The test used in this research is the lift ratio. The results of this study are publications in international journals that are in the draft process. Apart from that, the results of this study provide information on the analysis of patterns of lending books in libraries using the FP-Growth method. The resulting pattern is 103 patterns with a support count value of 5 and a confident 10% with the 2 itemset rule, this means that the level of book borrowing is still low. While the results of the analysis of the suitability of books in the study program with the borrower were 31% in accordance with the study program, namely Pharmacy and Public Health Sciences, meaning that there were 69% of students who borrowed books from the library that were not in accordance with their study program.

Sistem Pengambilan Keputusan Penentuan Pemasok Obat Pada Apotek Al Fayadh Farma Yogyakarta dengan Metode Topsis Eka Bagus Saputro; Anna Hendri Soleliza Jones
Jurnal Sarjana Teknik Informatika Vol 8, No 3 (2020): Oktober
Publisher : Teknik Informatika, Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12928/jstie.v8i3.17702

Apotek merupakan tempat yang dapat digunakan untuk menyalurkan dan memberikan informasi obat yang lengkap kepada masyarakat. Kendala dapat terjadi dalam penyediaan obat di apotek, seperti dalam memilih pemasok obat yang mampu memberikan pelayanan terbaik bagi apotek dari segi harga maupun jasa. Sehingga kinerja dari apotek dalam pemesanan obat ke pemasok obat masih belum efisien. Oleh karena itu, sangat diperlukan sistem pengambilan keputusan penentuan pemasok obat di apotek Al Fayadh Farma Yogyakarta dengan metode TOPSIS agar kinerja apotek lebih efisisen. Sistem pengambilan keputusan penentuan pemasok obat ini memerlukan 20 data pemasok dan 100 data obat yang didapatkan pada saat wawancara yang akan dimasukan ke dalam perhitungan metode TOPSIS dengan kriteria nilai harga pemasok, nilai stok barang, nilai layanan pengiriman, dan nilai sistem pembayaran sesuai proses bisnis yang telat dibuat. Sistem dirancang sesuai dengan permintaan dari apotek dan terakhir pengujian sistem tersebut diuji berdasarkan tampilan dan hasil akhir oleh pemilik apotek. Hasil dari penelitian yang dilakukan adalah sistem pengambilan keputusan dengan metode TOPSIS dapat merekomendasikan pemasok obat dengan ketentuan kriteria yang diinginkan dengan meranking atau merekomendasikan 5 pemasok obat teratas sesuai dengan kriteria masing masing dari pemasok obat tersebut. Dengan pengujian akurasi didapatkan sebesar 80%.

Implementasi Metode CART untuk Klasifikasi Diagnosis Penyakit Hepatitis Pada Anak Anna Hendri Soleliza Jones; Muhchromin Sucron Makmun
Journal of INISTA Vol 3 No 2 (2021): Mei 2021
Publisher : LPPM INSTITUT TEKNOLOGI TELKOM PURWOKERTO

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20895/inista.v3i2.265

Penyakit hepatitis adalah salah satu ancaman kesehatan utama di dunia. Hepatitis merupakan peradangan pada hati yang biasanya disebabkan oleh virus hepatitis. Berdasarkan hasil riset kesehatan dasar kementerian RI tahun 2014, diperkirakan 10 dari 100 orang Indonesia terinfeksi hepatitis. Menurut Direktur Jenderal Badan Organisasi Kesehatan Dunia (WHO), Tedros Adhanom Ghebreyesus hanya ada 1 dari 10 orang yang pernah melakukan tes hepatitis dan hanya 1 dari 5 orang yang mendapatkan pengobatan hepatitis yang tepat dimana hepatitis A justru lebih sering menyerang anak-anak, terutama yang tinggal di area dengan sanitasi rendah. Penelitian bertujuan untuk membangun sistem aplikasi berbasis komputer dalam menentukan klasifikasi diagnosis penyakit hepatitis dengan metode CART. Data yang digunakan merupakan data dua tahun terakhir dari RSUD Sei Bahar yaitu sebanyak 240 data. Prinsip dari metode CART adalah memilah seluruh amatan menjadi dua gugus amatan dan memilah kembali gugus amatan tersebut menjadi dua gugus amatan berikutnya. Hasil klasifikasi menggunakan metode CART sebagai pengetahuan menentukan penyakit hepatitis. Dengan menggunakan 35 data uji, dan analisis rekomendasi dari pakar, didapatkan bahwa metode CART dapat digunakan sebagai metode pengklasifikasian pada penyakit hepatitis dengan tingkat akurasinya sebesar 94%.

Fp-Growth Algorithm For Searching Book Borrowing Transaction Patterns And Study Program Suitability Lisna Zahrotun; Anna Hendri Soleliza Jones
IJISTECH (International Journal of Information System and Technology) Vol 5, No 5 (2022): February
Publisher : Sekolah Tinggi Ilmu Komputer (STIKOM) Tunas Bangsa

The current development of data has reached a sizeable amount. This is due to the development of the world of information technology which consists of data in it. One technique that can handle abundant data is data mining. Data mining methods are widely used to perform large amounts of data analysis. In the academic field, analysis can be used to determine the patterns of students and lecturers. Whereas in library transactions, analysis can be carried out to determine the patterns of existing book borrowing. This is done to determine the tendency of students with certain study programs to borrow any uku transactions. In this study, the aim of this research is to analyze the patterns of borrowing books from the Ahmad Dahlan University library, which includes borrowing transaction data and the book owner's study program. In addition, in this study, a percentage analysis of the suitability of the book borrower study program and the book owner's study program was also carried out. The stages in this research include data collection, data cleaning, data selection, data transformation, searching for association patterns using the FP-Growth method and pattern evaluation. The test used in this research is the lift ratio. The results of this study are publications in international journals that are in the draft process. Apart from that, the results of this study provide information on the analysis of patterns of lending books in libraries using the FP-Growth method. The resulting pattern is 103 patterns with a support count value of 5 and a confident 10% with the 2 itemset rule, this means that the level of book borrowing is still low. While the results of the analysis of the suitability of books in the study program with the borrower were 31% in accordance with the study program, namely Pharmacy and Public Health Sciences, meaning that there were 69% of students who borrowed books from the library that were not in accordance with their study program.

Case Based Reasoning using K-Nearest Neighbor with Euclidean Distance for Early Diagnosis of Personality Disorder Anna Hendri Soleliza Jones; Cicin Hardiyanti
IJISTECH (International Journal of Information System and Technology) Vol 5, No 1 (2021): June
Publisher : Sekolah Tinggi Ilmu Komputer (STIKOM) Tunas Bangsa

A personality disorder is a condition of a person with an extreme personality that causes the sufferer to have unhealthy and different thoughts patterns and behavior from other people. The personality disorders discussed in this study consisted of 110 diseases with 300 case data and 68 symptoms. Based on Basic Health Research (Riskesdas) 2018 data, it shows that more than 19 million people aged 15 years and over were affected by mental-emotional disorders. Data from the Statistics Indonesia in 2019 that the population of Indonesia is around 265 million people, while according to the Indonesian Clinical Psychologist Association, the number of verified professional psychologists is 1,599 clinical psychologists out of a total membership of 2,078 as of January 2019. However, this figure does not meet the standards of the World Health Organization (WHO), which is that psychologists serve 30 thousand people. This shows that Indonesia still lacks around 28,970 psychologists. The unequal distribution of professional psychologists has made psychologists need a long time to provide a diagnosis because of the number of patients being inversely proportional to the availability of psychologists in Indonesia. Moreover, there is not enough patient knowledge about the symptoms they feel. This study aims to produce a system for diagnosing personality disorders. This study is a case based reasoning to solve problems that have occurred in previous cases using K-Nearest Neighbor to classify data based on the closest distance using the calculation of the Euclidean Distance. Algorithm testing for the system used the Confusion Matrix test. Based on the results of testing data in the 60 case data using K-nearest Neighbor and the calculation of the Euclidean Distance with a score of K=3, it is known that 60 data have 100% similarity to cases with a personality disorder. Meanwhile, testing new cases with 10 case data that were not in the knowledge base was also conducted showing that 9 cases had 100% similarity to the previous case, while another case had 90% similarity to the previous case.

Sistem Pendukung Keputusan Dalam Pemilihan Makanan Pada Kulit Berjerawat Menggunakan Metode Certainty Factor (CF) dan Weighted Product (WP) Aditya Pramudita Kuncoro; Anna Hendri Soleliza Jones
Jurnal Sarjana Teknik Informatika Vol 10, No 3 (2022): Oktober
Publisher : Teknik Informatika, Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12928/jstie.v10i3.25210

Jerawat merupakan salah satu penyakit yang terjadi pada wajah dan memiliki tingkat keparahan yang berbeda. Jerawat banyak sekali faktor penyebabnya salah satunya merupakan makanan. Penelitian ini berfokus pada mendiagnosa jenis jerawat yang dialami serta tingkat keparahan jerawatnya dan memberikan alternatif berupa makanan yang dapat mengurangi jerawat.Penelitian ini menggunakan data yang di dapat melalui pakar kulit dan pakar gizi. Pengambilan data dilakukan dengan wawancara dan studi pustaka. Dari data yang di dapatkan oleh pakar kulit berupa data jerawat, gejalanya dan tingkat keparahan untuk di terapkan ke dalam sistem dengan menggunakan metode certainty factor. Serta data yang di dapatkan dari pakar gizi berupa data makanan yang dapat mengurangi jerawat yang akan diperingkatkan berdasarkan tingkat keparahan jerawat menggunakan metode weighted product.Penelitian ini menghasilkan sebuah sistem berbasis website yang memiliki 2 fitur utama yaitu diagnosa jenis jerawat serta rekomendasi makanan. Poses pengujian sistem ini menggunakan 4 pengujiian yaitu System Usability Scale (SUS), Validitas, Expert judgment dan Blackbox. Pengujian System Usability Scale (SUS) dan uji validitas dilakukan oleh 20 responden yang sedang berjerawat memiliki gejala yang berbeda dengan mendapatkan skor 89% untuk uji SUS dan uji validitas 85% dari pakar kulit. Pengujian menggunakan expert judgment dilakukan oleh pakar gizi dan pakar kulit menghasilkan 1 butir pernyataan hasil 0,875, menghasilkan sistem yang memiliki validitas tinggi, 4 pertanyaan memiliki indeks 0,75 dan 6 pertanyaan memiliki indeks 0,625 menghasilkan sistem yang memiliki validitas sedang bagi pengguna.

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